cuTile Python is a programming language designed for NVIDIA GPUs that simplifies the process of writing and deploying GPU kernels. It leverages CuPy for array manipulation and requires the CUDA Toolkit version 13.1 or higher. Users can install cuTile via the `pip install cuda-tile` command. The library includes a C++ extension, so a C++17-capable compiler, CMake 3.18 or later, and other build tools are necessary. For Debian-based systems, specific commands are provided to install the required dependencies without pulling in the full CUDA Toolkit. An example kernel demonstrates how to perform vector addition using cuTile. The kernel runs in parallel on the GPU, employing a tile size of 16. Input arrays are generated randomly, and after launching the kernel, the results are compared to ensure accuracy. Users can access more examples in the Samples and TileGym sections. The library is still evolving, with experimental features available for users willing to work from the source. Installing the experimental package allows access to new APIs that may change as they are developed. For testing, cuTile utilizes the pytest framework, with additional dependencies available through a requirements file. This setup allows users to run specific tests, ensuring functionality and stability. The project is licensed under the Apache 2.0 license, which permits modification and redistribution under certain conditions. Users are encouraged to check the prerequisites and follow the installation instructions carefully to avoid potential issues.